A debugging approach for Big Data applications in Pharo

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution


Big Data applications are more and more popular; they typically analyze big sets of data from different domains. Many frameworks exist for programmers to develop and execute their Big Data applications such as Hadoop Map/Reduce and Apache Spark. However, very few debugging support is currently provided in those frameworks. When an error hap- pens, developers are lost in trying to understand what happened from the information provided in log files. Alternatively, few solutions allow to replay the execution, but they are slow and time-consuming. In this paper, we present an online approach to debug Big Data applications. We first introduce Port, a framework on top of Hadoop Yarn that al- lows to deploy and execute Pharo Map/Reduce applications. We debug applications deployed on such framework using IDRA, a novel online debugger for Pharo applications. With IDRA the running application can be debugged in a centralized way, and the code of the application can be dynamically updated to fix bugs.
Original languageEnglish
Title of host publicationProceedings of the 13th Edition of the International Workshop on Smalltalk Technologies
Publication statusAccepted/In press - 2018


Dive into the research topics of 'A debugging approach for Big Data applications in Pharo'. Together they form a unique fingerprint.

Cite this